ITECH7407 Group Assignment: Big Data Analytics for Business Value

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Added on 2024/07/02

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This report explores the application of big data analytics in e-commerce, focusing on how it generates business value for companies like Amazon and Walmart. It examines the collection and processing of unstructured data from various sources to derive valuable insights, improve customer feedback, and reduce risk. The report identifies opportunities for big data, such as increased shopper analysis, improved customer service, and secure online payments, while also addressing challenges related to data availability, quality, velocity, and veracity. Current techniques and technologies for big data analytics are discussed, highlighting their role in building new capabilities and facilitating decision-making within the chosen industries. The analysis shows how Amazon and Walmart leverage big data initiatives to enhance their operations and customer experience, ultimately contributing to their market dominance. This assignment solution is available on Desklib, where students can find past papers and solved assignments.

REAL-TIME ANALYTICS [ITECH7407]
GROUP ASSIGNMENT
ON
Big Data and Analytics to Increase Business Value
Organizations:
SUBMITTED TO:- SUBMITTED BY:-
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Executive Summary:
The aim of this research is the collection of unstructured data from different sources such as
mobile and internet, process it to get valuable information and analysing the data to get the
useful insights of the e-commerce. A lot of literature review was done on the previous studies
to accomplish this aim. The major task in the research is to study the generation of data in 2
industries and evaluate the technologies and techniques of Big Data analytics that can give
advantages to the companies like improved customer feedback and reduced risk prevention.
For the completion of this task, Big Data analytics is used to create business value for
Amazon and Walmart.
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Table of Contents
Executive Summary:.................................................................................................................. 2
1. Introduction to Big Data.........................................................................................................5
Big data in Amazon and Walmart.......................................................................................... 6
2. Opportunities for the Big Data............................................................................................... 7
2.1 Increased Shopper Analysis:............................................................................................ 7
2.2 Improved Customer Service:............................................................................................8
2.3 Easier and more secure online payments:........................................................................8
2.4 Continued advances in mobile commerce:...................................................................... 8
3. Challenges faced by the Big Data in e-commerce...............................................................10
3.1 DATA:............................................................................................................................10
3.1.1 Data Availability:.................................................................................................... 10
3.1.2 Data quality:............................................................................................................ 10
3.1.3 Velocity:.................................................................................................................. 10
3.1.4 Veracity:.................................................................................................................. 10
3.1.5 Data Discovery:.......................................................................................................10
3.1.6 Relevance:............................................................................................................... 10
3.1.7 Personally Identifiable Information:.......................................................................10
3.1.8 Data Dogmatism:.................................................................................................... 11
3.2 PROCESS:.....................................................................................................................11
3.3 MANAGEMENT:..........................................................................................................11
4. Current techniques and technologies for Big Data Analytics..............................................13
Big Data analytics technique and application for e-commerce............................................14
Big data technologies for e-commerce.................................................................................15
5. The value added to each chosen industry by the Big Data initiative from building new
capabilities and facilitate decision-makers...............................................................................17
Walmart:...............................................................................................................................17
Amazon:............................................................................................................................... 18
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Conclusion................................................................................................................................19
References................................................................................................................................ 21
List of Figures
Figure 1: Big Data using Top 10 Companies.............................................................................5
Figure 2: Key Befits of analytics in big data..............................................................................7
Figure 3: Opportunities for the Big Data...................................................................................9
Figure 4: Challenges faced by the Big Data in e-commerce....................................................12
Figure 5: Data growth in between 1986 and 2007...................................................................13
Figure 6: Big Data analytics technique and application for e-commerce................................15
Figure 7: Review of social media analytics process and Big Data pipeline............................16
Figure 8: How Supply Chain Flagship Newsletter..................................................................17
Figure 9: How Walmart Makes Money? Understanding Walmart Business Model...............18
Figure 10: How Supply Chain Flagship Newsletter................................................................19
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1. Introduction to Big Data
Big data is basically the huge and complex data sets where a large amount of data is present.
The data includes a lot of information including social media analytics, data management
capabilities and real-time data. The requirement of the big data is originally generated for the
big companies like Facebook, Google and Yahoo etc.
Figure 1: Big Data using Top 10 Companies
Source: educationview, 2018
The new tools are added to the management of the Big Data to improve the handling and the
storage of the data. The new Big Data technology is both economically and technically
feasible. The new technology management can allow not only to store the huge data sets but
also to analyse the datasets to get a better insight into the information. The basic functions of
the Big include collection, storing, analysing and visualizing the huge volume of the data.
The collection of raw data is done from mobile devices or any other media collection device
and it is the common challenge faced by most of the organizations (Russom, 2011). A good
platform for Big Data can allow developers to ingest a variety of data varying from structured
to un-structured at any available speed which is available at a real time. A secure, durable and
scalable platform constitutes a good platform for fulfilling all the requirements of the Big
Data. The unstructured data is converted into meaningful data once it reaches the analysing
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state. The process of joining the data, aggregating the data using some of the advanced
functions comes under the analysing state (Jain, & Suryavanshi, 2017). The platform of the
Big Data provides data to the business stakeholders through agile visualization of the data
that makes the data easily accessible to the user. The type of analytics used can help the end-
user to get the best available statistical predictions and any recommendation action. This
makes the use of the Big Data optimal for the end users.
Big data in Amazon and Walmart
Huge e-commerce companies like, Amazon has improved its performance by utilizing the
Big Data available from its customer. As one of the dominant company in the market
Amazon has one of the biggest databases of the customer’s information. Though, Amazon
has started as a retailer brand but now Amazon started providing online entertainment store as
“Amazon Prime” which enabled users to get movies, television shows and series by just
taking membership through the Amazon channel. The tastes, preferences and the purchasing
history of the customers constitute a huge amount of information. Amazon improved its
customer care quality using the correct Big Data resources. Walmart is another big name in
the business of retail. It has 245 million customers who visit 10,900 stores of Walmart stores
across the globe. The data from the Walmart’s customer is handled by the Inkiru which helps
in the marketing, merchandising, and the fraud prevention of the Walmart across the globe
(Gupta, et. al., 2014).
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2. Opportunities for the Big Data
In the world of emerging technology, everything that is done online or offline is a source of
data. Along with the increasing, the creation of the data, the tools to manage the data is also
developed. The data generation is reached to a point where the generated data is too much
data. The understanding of the data has become more complicated as the data leaves us with
various facts, perceptions, numbers, and percentages (Zhou, et. al., 2014). The concept of Big
Data is quite complex and it is not yet understood by many of the organizations. Big Data has
a great influence on the retail market and it influences them in many ways. Some of the
opportunities that are provided by the Big Data to the retail organizations like Amazon and
Walmart are mentioned below:
49.0%
16.0%
10.0%
9.0%
9.0% 6.0%
Chart Title
1
2
3
4
5
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Figure 2: Key Befits of analytics in big data
2.1 Increased Shopper Analysis: It is very important for the business to understand the
behaviour of the shopper so that the business can grow. One of the essential parts of the
business success process is the management of the Big Data. It can provide data like the
ongoing trend in the market, any spike in the demands of the product and the preferences of
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the customer (Zhou, et. al., 2014). The business can make the most popular product available
to the customer and market them for increasing the sale of the product based on the data
provided by the analysis of the Big Data. There are some products that are not available on
the website but customer tries to search them, then the Big Data will help to understand those
searches and help Amazon or Walmart grab the new opportunities in the market.
2.2 Improved Customer Service: The numbers which show the unhappy and unsatisfied
with the customer service are relatively high and alarming for both Amazon and Walmart.
91% of the unhappy customer opts out of continuing the shopping on e-commerce if they are
experienced with poor customer service experience. The more predictive side of the Big Data
can be used by Amazon and Walmart will help the companies to identify the problem in their
service and can positively solve the existing issues even before a customer can involve with
the company (Zhou, et. al., 2014).
2.3 Easier and more secure online payments: The role of the Big Data can be very
significant in the secure payment on the online websites of Amazon and Walmart. All the
different payment methods are integrated into one platform so that the payment option for the
users becomes easier and it also helps in reducing the risk of fraud. The fraud in the payment
gateways are identified at real time and the strong advanced analytics provides a proactive
solution for the identification and the prevention of frauds.
2.4 Continued advances in mobile commerce: The use of the mobile phones is increasing
day by day with the increasing population. The use of mobile phone has reached a point
where researchers predicted that the use of the desktop computers is declining and at some
point, it will become obsolete. Big data is an advanced tool that provides the mobility in the
field of e-commerce. The data can be collected from different sources by the companies and
the collected data can be analysed that will benefit the e-commerce companies (Bohrer,
2018).
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Figure 3: Opportunities for the Big Data
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Increased Shopper Analysis
Improved Customer Service
Easier and more secure
online payments
Continued advances in
mobile commerce

3. Challenges faced by the Big Data in e-commerce
Each day, about 2.5 quintillion bytes of data is generated from the e-commerce. The data is
generally coming from videos, pictures, the posting on the social media, different sensors,
records of the purchase, GPS signals from mobile etc. There are challenges to the Big Data in
data collection, processing of the data and the management of data (Zhou, et. al., 2014).
Some of the challenges faced by Amazon and Walmart are mentioned below:
3.1 DATA:
The challenges faced in the field of Data for e-commerce are:
3.1.1 Data Availability: The availability of data is a major part for any company. The
companies like Amazon and Walmart hugely depends on the data for their decision making
or planning for the future. The companies can take a bad decision based on bad data.
3.1.2 Data quality: The questions on the quality of data like the goodness of data, the
broadness of data covered, fineness of the sampling resolution and the timeliness readings all
together decide the quality of the data (Kwon, et. al., 2014).
3.1.3 Velocity: It is generally the speed at which the data is retracted by the application for
the user. The faster the availability of data the easier it becomes for any company to make
decisions based on that data.
3.1.4 Veracity: The data can sometimes be missing some of the important parts. Sometimes
uncertainty, misstatements, untruths and imprecision can cause the bad decision making by
the companies. So it is very important for the Big Data service providers to give the accurate
and precise data to the user.
3.1.5 Data Discovery: A lot of huge data sets are collected across the web which makes it
crucial to take out the meaningful and high-quality data from the unstructured data.
3.1.6 Relevance: When a user search for some data on the web or from the huge data sets
presents on the Big Data servers, the user expects a relevant data for his search. The service
providers should keep in mind that the data retrieved should not be un-relevant to the topic in
order to give the user complete information (Zhou, et. al., 2014).
3.1.7 Personally Identifiable Information: Most of the information that is searched about
the people can compromise the privacy of them. So the data service providers must integrate
the security modules so as to extract enough information that will not harm the privacy of
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other people. Some part of this should have an oversight of the government to preserve the
privacy of the people.
3.1.8 Data Dogmatism: Today most of the companies take help of the data analytics from
the Big Data but the companies should not be too dependent on this analytics for their big
decisions. Common sense and domain experts should take part in the decision making for the
big companies.
3.2 PROCESS:
There are various challenges that come up during the derivation of the useful and meaningful
insights from the data. Some of this includes the correct capturing of data from different
sources. The next step after data collection is the alignment of the data in a suitable form. For
example, resolving the issue of data duplicity when two datasets are the same. Then, the
transformation of this data into a form that can be used for analysis. The modelling is done
after that either mathematically or through some type of simulation. At last the visualization
and the sharing of the resultant output for the end user (Kwon, et. al., 2014).
3.3 MANAGEMENT:
The data privacy, data security and the correct governance of the gathered data comes under
the management of the Big Data. E-commerce companies like Amazon and Walmart face
challenges in this also as the data should be used correctly. Using the data correctly means
that it is abiding by all the rules and its intended use. Companies should track the usage of
data, how it is derived and transformed along with managing the lifecycle of the data ( Kwon,
et. al., 2014).
Amazon and Walmart are required to manage the data properly as there are legal and ethical
concerns attached to the data. These organizations should also make the data secure, access
controlled and it should be logged for audits.
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Figure 4: Challenges faced by the Big Data in e-commerce
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Challenges faced by the Big
Data in e-commerce
DATA
Data Availability
Data quality
Velocity
Veracity
Data Discovery
Relevance
Personally Identifiable
Information
Data Dogmatism
PROCESS
MANAGEMENET